Rionel Belen Caldo

Design, development and implementation of a fuzzy logic controller for DC-DC Buck and Boost converter in an FPGA

A fuzzy logic controller for DC-DC Buck and Boost converters is designed and presented in this paper. The mathematical model of buck and boost converter and fuzzy logic controller are first derived then converted to a hardware model using VHSIC Hardware Description Language. The hardware model was subsequently synthesized and implemented in a Field programmable Gate Array (FPGA) chip. In order to confirm that the mathematical model gives stable output frequency, simulation on MATLAB is made. To verify the effectiveness of the simulation model, an experimental set up is developed. An FPGA-based fuzzy logic controller was implemented and interfaced to a DC-DC converter module. The system was tested using white LEDs as loads. Simulation and experimental results show that the DC-DC converter is able to maintain the output based on the value set inside the controller module.

Fuzzy logic control of water quality monitoring and surveillance for aquatic life preservation in Taal Lake

The concept and application of fuzzy logic is becoming a vital tool in addressing the issues of environmental science and policy. It seemed to be a common practice to deal constantly with linguistic terms-not acceptable, just acceptable, acceptable, highly acceptable, etc. Considering its importance in risk assessment, the applications of fuzzy logic is still rarely used in other environmental assessments. This is mainly because few researchers conduct study in view of aquatic life preservation and sustainability. This paper considers the use of fuzzy logic in the assessment of water quality in Lake Taal of Batangas. The goal of the study is to design a fuzzy-based water quality assessor in excel VB macro program platform.

ANN Diagnosis for Defect Detection and Classification in Two-Layer Printed Circuit Boards Using Supervised Back-Propagation Algorithm

In this work, the proponent makes use of Artificial Neural Network (ANN) to visually inspect and classify the defect found in two-layer Printed Circuit Boards (PCBs). The proponent trained and tested the data for pattern recognition using C language. The supervised back-propagation learning algorithm was used for training and testing of PCB patterns. This learning algorithm is suitable for training multi-layered neural network and for generating the deltas of all output and hidden neurons. Considering that training and testing the data would only provide outputs with respect to generated weights, the proponent makes use of another program for defect detection. Excel VBA macro program was used for commonality testing of actual versus expected outputs. Also, it was used in making PCB defect detection possible by marking each defective unit. The proponent modeled a bare PCB circuit with 80 × 44 dimensions. The PCB board was further divided into 32 panel sides, each with 10 × 11 dimensions. There were five defective units modeled in the first layer and there were 14 classified defects used in the second layer. These data were trained and tested successfully, accurately and reliably using ANN.

An Intelligent PCB Visual Inspection System for Defect Detection and Localization in Excel VBA Macro

An intelligent system using Excel VBA macro program was made in this research. The proponent modeled a bare Printed Circuit Board (PCB) pattern used by Moganti et al. and Khalid in 2008. The proponent represented this PCB bare circuit in 80 × 44 dimensions with bits of ‘0-blank image’ and ‘1-filled/black image’. The PCB pattern was further divided into 32 panels in 10 × 11 dimensions with same bit representation. This bare pattern was compared with defective units for template matching using logical operators. The proponent considered building the system in high-level programming type of language. Considering that the system’s algorithm would require the use of Graphical User Interface (GUI) for visualization purposes. Excel VBA macro program, in this accord, was preferred by the proponent as it provides powerful tools both in GUI constructions and in Microsoft Excel applications. As the study aims to provide a more systematic way of inspecting PCB for defect detection, the system is built with functionalities capable of handling and mimicking the tasks of PCB visual inspector. The system would not only detect occurrence/s of defect/s, rather it would provide defect analysis by localizing the exact location of the defect on a specific panel and assessing defect likelihoods using repository and trend chart.

Development of a Remote Controlled Mobile Robot for Toy Application Using RF Module in PIC Microcontroller

Designed, developed and presented in this paper is a remote controlled mobile robot for toy application using RF module in PIC microcontroller. The goal of this study is to provide a reliable way of communication over a Wi-Fi network for mobile robot using Radio Frequency (RF) wireless communication module. The proponents make use of model-based task allocation method. This effective task allocation method is made possible thru central commanding computer, which realizes reliable operation for identified tasks. The proponents built a mobile robot, with capability of responding to three simple movements: forward, turn left and turn right. The proponents make use of PIC microcontroller as its control unit and it was programmed using C++. The mobile robot will communicate with a central commanding server, which is to be controlled over RF wireless communication. Through a local area network, the computer will send the command movements to the mobile robot using RF module.

FLC-Based Indoor Air Quality Assessment for ASHRAE Standard Conformance

Designed and presented in this paper is Indoor Air Quality Assessment using fuzzy logic technology. Triangular membership functions for classified Air and Gaseous parametric categories are to be constructed in Matlab Fuzzy Logic Toolbox using ASHRAE, EPA and WHO standards. Air parameters include Temperature (T) and Relative Humidity (RH) while Gaseous parameters include Carbon Monoxide (CO) and Carbon Dioxide (CO2). The parameters are to be classified as Very Good (VG), Good (G), Fair (F), Poor (P) and Very Poor (VP). The Sugeno-style of inference systems is utilized in this proposed to describe the fuzziness of assessing indoor air quality. There were 131 fuzzy rules formulated. The output parameter is classified as Highly Acceptable (HA), Acceptable (A), Just Acceptable (JA), Not Acceptable (NA), and Highly Not Acceptable (HNA). The fuzzy-based system is simulated and the results were further verified using the weighted means of 90 generated data samples.

Design and Development of Audit Central Data Bank at Ibiden Philippines, Inc. (IPI)

In most of the companies in the Philippines, audit findings and results are monitored manually. This method offers inaccessible and unreliable data that invokes downtime in audit issuance, audit response, audit verification and implementation, and audit closure as well. It showcased a process system of less priority and consideration on Productivity, Quality, Cost, Delivery and Morale. The proponent thought of a way to develop a central repository or data bank of audit findings to easily retrieve the audits conducted by IQA, PQA, IEA, TPM and other auditing bodies and to provide robust monitoring of Audit Issuance, Audit Response, Audit Verification (Verification of Implementation) and Audit Closure (Verification of Effectiveness). Audit Central Data Bank in Ibiden Philippines, Inc. is a PC-based centralized macro program. It is software that consolidates all audit results of each auditing body (IQA, PQA, IEA, TPM, YIP and External Supplier). It performs common tasks and functions understood and applied by entire IPI community.